A range of modalities are available for acquiring and constructing images of physical subjects. In the medical imaging field, such modalities include magnetic resonance imaging systems, commonly referred to generically MRI systems. MRI systems generally include magnetic field-generating coils which can be carefully controlled to excite gyromagnetic material in a subject of interest. Proper control of a plurality of magnetic field-generating coils, such as field gradient coils, excitation coils, and so forth, permit the gathering of an increasing number of image types, allowing an attending physician or radiologist to concentrate on specific features of interest in the subject. During complex data acquisition sequences in such systems, a large number of precisely controlled pulses may be generated and coordinated with one another to produce the desired fields, and to sense emissions from the subject, typically produced by the exited gyromagnetic material of internal static or dynamic tissues.
In a number of imaging modalities, a large amount of data is acquired through a series of programmed steps. The data acquisition sequences are typically pre-established in software routines stored in a controlling computer system. The attending physician or radiologist selects desired image types or protocols and sets certain parameters employed by the controlling computer during the imaging process. Thereafter, the computer executes a series of steps, typically in repetition, to acquire the image data. In MRI processes, for example, magnetic and radio frequency pulses are typically emitted for a plurality of axes to excite specific volumes of tissue. The pulses are interlaced with acquisition sequences wherein emissions from the tissue are sensed and encoded for later filtering and image reconstruction.
Although at a high level the user of such imaging systems may simply select a particular image type or configuration, the selected configuration includes a large number of parameter control steps which are not necessarily apparent to the user. In MRI systems these include specific axis pulse sequences, such as for orienting magnetic fields, exciting tissues, and acquiring data. Each of these sequences, in turn, includes selections of a variety of parameters, such as pulse duration, pulse amplitude, timing between pulses, and timing of emission detection. Moreover, the image sequences may include coordinated pulse trains which follow one another in a logical manner consistent with the physical constraints of the material being imaged and the modality employed. For example, MRI applications may include pulse trains intended to excite specific locations within a subject, orient fields for slice selection, flip directions of rotation of gyromagnetic material, and so forth. Finally, periods between activity may be programmed, such as to permit settling of equipment or to allow time for processing of signals.
In general, programmers designing specific imaging sequences attempt to coordinate the many parameters of such multi-axis activity in such a way as to reduce the overall image data acquisition time, while avoiding unwanted interactions between the segments of the acquisition sequence which might result in a less useful image. However, while manual configuration of image acquisition sequences has provided a useful array of imaging techniques, it is not without drawbacks. For example, as multi-axis control in MRI and other imaging systems becomes increasingly complex, so does the configuration of the control sequence for the axes and the coordination between sequences of activity on the axes. Moreover, further optimization of image data acquisition is often hampered by the need to foresee complex interactions between axis activity. Failure to anticipate such interactions can result in control of specific parameters in ways that do not render the desired image data or which do not permit appropriate time for data collection or processing.
There is a need, therefore, for an improved technique for defining control sequences in imaging systems, such as MRI systems. In particular, there is a need for a technique for coordinating and optimizing pulse sequences and other activities on multiple axes in an imaging system, and which inherently respects the physics of the image data acquisition process, and avoids unwanted interactions between activities on multiple axes.